Traditionally, customer relationship management systems have leveraged vendor specific Automatic Call Distributor (ACD) methods for routing of traditional channels such as voice. These methods are more appropriate for voice channels, however, and typically use parameters such as Automatic Number Identification/Dialed Number Identification Service (ANI/DNIS) and Customer Relationship Management (CRM) data related to the subscriber/caller for routing the voice calls to the appropriate agent. The agent has a front end which is typically integrated with back end systems for providing details about the caller to enable the agent to appropriately understand the call-related interaction. Additionally, in an event of multi-channel handling such as email and Short Message Services (SMS), these are typically treated as non-interactive channels, and are routed to agents leveraging various algorithms including a blended way to handle incoming/outgoing traffic across the channels thereby optimizing agent time.
With the emergence of social media channels and the dynamic nature of online feedback through blogs, wikis, Tweets and other internet-based communities, customers are able to reach out widely to share feedback regarding products and service experiences. Unlike traditional channels, such as voice/video calls, feedback from social media channels is instantaneous, and hence the ability of the agent to respond quickly to such feedback for the enterprises is crucial.
Hence, it is important to effectively and quickly treating inputs from social media channels in the context of a “Multi-Channel Interaction” center. This implies that the treatment of inputs from social media channels has to be different from conventional methods that have been adopted for non-interactive channels, such as SMS and email, and traditional channels, such as voice, chat and the like. Typically, the feedbacks/comments from the social media channels are obtained through crawlers. The posts/feedback/comments obtained through crawlers are used as input to perform the sentiment analysis. Based on the sentiment analysis, the posts/feedback/comments are handled by social media relationship platforms which are an extension of the traditional customer relationship management systems.
The currently available method employed in Services for Computer Supported Telecommunications Applications (CSTA)-supported Fixed Mobile Convergent infrastructure does not facilitate a mechanism to treat relevant additional routing/key parameters applicable for social media within the CSTA specification. This limitation can be overcome through a separate non-CSTA-based mechanism for such treatments. This results, however, in additional costs/infrastructure to the existing CSTA-supported infrastructure. Additionally, this limitation on CSTA-supported infrastructure restricts the balanced treatment of Social Media Interactions vis-à-vis other interactions by having common priorities across the different channels.
Accordingly, there exists a need to provide methods and systems that address these challenges effectively in a Multi-Channel Fixed Mobile Convergent infrastructure, leveraging CSTA through suitable enhancements.